Senior ERP Specialist

Sapsf; Mountain View (CA); On-site; USD 150,000 - 190,000; Full time

Job summary

Google is seeking a Data Engineer (AI/ML Focus) to design and optimize data pipelines on Google Cloud Platform, enabling scalable AI applications. You will build robust data architectures, ensuring data quality and accessibility for model training and deployment.

You will collaborate with Data Scientists, Engineers, and Product Managers, implement MLOps practices, and stay current with Vertex AI, Dataflow, and related services to drive innovative AI solutions.

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Engineering, or a related quantitative field.
• Proven experience as a Data Engineer, with a strong focus on building data solutions for AI/ML applications.
• In-depth knowledge and hands-on experience with Google Cloud Platform (GCP) data services (BigQuery, Dataflow, Dataproc, Cloud Storage, Cloud Composer, etc.).
• Strong proficiency in programming languages such as Python (essential), and experience with Scala or Java is a plus.
• Expertise in SQL and experience with various database technologies (relational, NoSQL, data warehouses).
• Familiarity with machine learning concepts, algorithms, and workflows (e.g., feature engineering, model training, evaluation, deployment).
• Experience with machine learning frameworks like TensorFlow or PyTorch.
• Understanding of distributed systems, big data technologies, and real-time data processing.
• Experience with version control systems (e.g., Git) and CI/CD practices.
• Excellent problem-solving, analytical, and communication skills.
• Google Cloud Professional Data Engineer certification is a strong plus.

Responsibilities

• AI/ML Data Preparation: Collaborate closely with Data Scientists and Machine Learning Engineers to understand data requirements for model training, evaluation, and serving. Prepare, transform, and curate large, diverse datasets (structured, unstructured, streaming) to optimize them for AI/ML workloads.
• AI/ML Services: Gemini AI, AI Studio, Vertex AI (for model training, deployment, MLOps, Pipelines, Workbench, AutoML). Should be able to create prompts and build applications using AI studio.
• Automation & MLOps: Automate data processes, develop CI/CD pipelines for data and ML models, and contribute to MLOps best practices for seamless deployment and monitoring of AI/ML solutions. Monitor, troubleshoot, and optimize the performance and cost-effectiveness of data pipelines and AI/ML infrastructure.
• Collaboration & Communication: Work effectively with cross-functional teams, including Data Scientists, Analysts, Software Engineers, and Product Managers, to understand data needs and deliver impactful solutions.
• Innovation & Research: Stay up-to-date with the latest advancements in data engineering, AI/ML, and GCP technologies, continuously exploring and recommending new tools and approaches.

Skills

Python

SQL

CI/CD

Distributed systems

Communication

MLOps

TensorFlow/PyTorch

Education

Bachelor's or Master's degree in Computer Science, Data Engineering, or related field

Tools

BigQuery

Dataflow

Dataproc

Cloud Storage

Cloud Composer

Git

Job description

Requisition ID174598-Posted09/29/2026

Data Engineer (AI/ML Focus) - Google Cloud Platform

We are seeking a highly skilled and experienced Data Engineer with a strong background in AI/ML to design, build, and optimize robust data pipelines and infrastructure on the Google Cloud Platform (GCP). The ideal candidate will be passionate about leveraging data to power machine learning initiatives, ensuring data quality, accessibility, and scalability for advanced analytics and AI applications.

Responsibilities

• AI/ML Data Preparation: Collaborate closely with Data Scientists and Machine Learning Engineers to understand data requirements for model training, evaluation, and serving. Prepare, transform, and curate large, diverse datasets (structured, unstructured, streaming) to optimize them for AI/ML workloads.
• AI/ML Services: Gemini AI, AI Studio, Vertex AI (for model training, deployment, MLOps, Pipelines, Workbench, AutoML). Should be able to create prompts and build applications using AI studio.
• Automation & MLOps: Automate data processes, develop CI/CD pipelines for data and ML models, and contribute to MLOps best practices for seamless deployment and monitoring of AI/ML solutions. Monitor, troubleshoot, and optimize the performance and cost-effectiveness of data pipelines and AI/ML infrastructure.
• Collaboration & Communication: Work effectively with cross-functional teams, including Data Scientists, Analysts, Software Engineers, and Product Managers, to understand data needs and deliver impactful solutions.
• Innovation & Research: Stay up-to-date with the latest advancements in data engineering, AI/ML, and GCP technologies, continuously exploring and recommending new tools and approaches.

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Engineering, or a related quantitative field.
• Proven experience as a Data Engineer, with a strong focus on building data solutions for AI/ML applications.
• In-depth knowledge and hands-on experience with Google Cloud Platform (GCP) data services (BigQuery, Dataflow, Dataproc, Cloud Storage, Cloud Composer, etc.).
• Strong proficiency in programming languages such as Python (essential), and experience with Scala or Java is a plus.
• Expertise in SQL and experience with various database technologies (relational, NoSQL, data warehouses).
• Familiarity with machine learning concepts, algorithms, and workflows (e.g., feature engineering, model training, evaluation, deployment).
• Experience with machine learning frameworks like TensorFlow or PyTorch.
• Understanding of distributed systems, big data technologies, and real-time data processing.
• Experience with version control systems (e.g., Git) and CI/CD practices.
• Excellent problem-solving, analytical, and communication skills.
• Google Cloud Professional Data Engineer certification is a strong plus.